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Bungee View Research Goals</title>
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<p>
Web search engines have attracted widespread demand for information
retrieval from unstructured documents. The number of structured and
semi-structured documents available on the Web is also huge, and
collections of these are more amenable to data mining.  Yet there has
been no similar explosion of interest in this kind of
exploration. Finding patterns in databases of political contributions,
environmental data, or hospital and school performance
would surely interest many citizens. The main research question for
this project is how to support such exploration for users with little
or no training in statistics or programming.  In contrast to other
data-mining systems, Bungee View focuses on learnability,
responsiveness, robustness, and providing a satisfying user
experience.
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<p>
Bungee View employs a novel kind of histogram that interactively
displays deviations from a null-hypothesis distribution, allowing
non-technical users to explore and discover underlying structure in the
data.  For each attribute it shows (i) the distribution
of items matching the current query and (ii) whether the distribution
is in accordance with the assumption that attributes are
independent. For instance, by querying to find photos whose Subject is
railroads and then looking at the distribution of Dates, it is
apparent that the fraction of photos in the collection with this subject has been
decreasing almost monotonically for the past century.
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<p>
In order to better understand the knowledge discovery needs of
non-technical users and to gain insights into how Bungee View might meet these
needs, we want to make it available to the general public.  Different
collections will appeal to different kinds of users.  In each case, we
will track their usage and solicit feedback via email.
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<div style="text-align: right;">
<a HREF="http://www.cs.cmu.edu/~mad">Mark Derthick</a>
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<i> Last update: 7 October 2006 </i>
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